Knowledge Commons of Institute of Automation,CAS
Decentralized guaranteed cost control of interconnected systems with uncertainties: A learning-based optimal control strategy | |
Wang, Ding1,3; Liu, Derong2; Mu, Chaoxu3; Ma, Hongwen1 | |
发表期刊 | NEUROCOMPUTING |
2016-11-19 | |
卷号 | 214页码:297-306 |
文章类型 | Article |
摘要 | A novel learning-based optimal control approach is constructed to attain the decentralized guaranteed cost controller design for a class of continuous-time complex nonlinear systems with dynamical uncertainties and interconnections. This is performed by combining robust decentralized control formulation with adaptive critic learning technique. By expressing the interconnected subsystems as a whole system and introducing a new cost function for the overall plant, the decentralized guaranteed cost control problem is formulated as an optimal control problem for the nominal overall system. Then, a policy iteration based learning control algorithm is employed to solve the modified Hamilton-Jacobi-Bellman equation with respect to the nominal plant iteratively. A critic neural network is constructed to approximate the optimal state feedback control law and then the uniform ultimate boundedness stability issue is analyzed. Meanwhile, a simulation experiment is conducted to verify the good performance of the control approach. (C) 2016 Elsevier B.V. All rights reserved. |
关键词 | Adaptive Dynamic Programming Decentralized Control Guaranteed Cost Control Interconnected Systems Learning Control Neural Networks Optimal Control Uncertain Plant |
WOS标题词 | Science & Technology ; Technology |
DOI | 10.1016/j.neucom.2016.06.020 |
关键词[WOS] | TIME NONLINEAR-SYSTEMS ; OPTIMAL-CONTROL DESIGN ; H-INFINITY CONTROL ; ROBUST-CONTROL ; POLICY ITERATION ; FEEDBACK-CONTROL ; HJB SOLUTION ; ALGORITHM ; PARAMETERS |
收录类别 | SCI |
语种 | 英语 |
项目资助者 | National Natural Science Foundation of China(61233001 ; Beijing Natural Science Foundation(4162065) ; Tianjin Natural Science Foundation(14JCQNJC05400) ; Research Fund of Tianjin Key Laboratory of Process Measurement and Control(TKLPMC-201612) ; Early Career Development Award of SKLMCCS ; 61273140 ; 61304018 ; 61304086 ; 61533017 ; U1501251 ; 61411130160) |
WOS研究方向 | Computer Science |
WOS类目 | Computer Science, Artificial Intelligence |
WOS记录号 | WOS:000386741300028 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/13374 |
专题 | 多模态人工智能系统全国重点实验室_复杂系统智能机理与平行控制团队 |
作者单位 | 1.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China 2.Univ Sci & Technol Beijing, Sch Automat & Elect Engn, Beijing 100083, Peoples R China 3.Tianjin Univ, Sch Elect Engn & Automat, Tianjin Key Lab Proc Measurement & Control, Tianjin 300072, Peoples R China |
第一作者单位 | 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Wang, Ding,Liu, Derong,Mu, Chaoxu,et al. Decentralized guaranteed cost control of interconnected systems with uncertainties: A learning-based optimal control strategy[J]. NEUROCOMPUTING,2016,214:297-306. |
APA | Wang, Ding,Liu, Derong,Mu, Chaoxu,&Ma, Hongwen.(2016).Decentralized guaranteed cost control of interconnected systems with uncertainties: A learning-based optimal control strategy.NEUROCOMPUTING,214,297-306. |
MLA | Wang, Ding,et al."Decentralized guaranteed cost control of interconnected systems with uncertainties: A learning-based optimal control strategy".NEUROCOMPUTING 214(2016):297-306. |
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